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Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Palanisamy T, Krishnasamy KN - PLoS ONE (2015)

Bottom Line: To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network.Finally, the Poly Distribute algorithm effectively distributes the sensor nodes.Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Nandha Engineering College,Erode, Tamilnadu.

ABSTRACT
Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

No MeSH data available.


Related in: MedlinePlus

Measure of time complexity.
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pone.0138932.g006: Measure of time complexity.

Mentions: To explore the influence of time complexity on BNEPD technique, simulations are performed by applying 350 different sensors with a network size of 1000 * 1000 m in a transmission range of 100 ms depicted in Fig 6. The BNEPD technique shows competitive results compared to the state-of-the-art methods, namely DRINA [1] and CBPS [2]. The Fig also shows that the time complexity drastically reduces and reaches its zenith compared to two other methods because of the application of Bayes principle where sensor nodes efficiently detects target objects of similar events by sending it back to the sink nodes. In addition, efficient data aggregation at the sink nodes using polynomial regression function further improves the data aggregation efficiency with the help of polynomial coefficient using Poly Distribution algorithm. The application of Poly Distribution Algorithm efficiently helps in minimizing the time complexity by 4–9% when compared to DRINA [1] and 8–17% when compared to CBPS [2] respectively.


Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Palanisamy T, Krishnasamy KN - PLoS ONE (2015)

Measure of time complexity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4591332&req=5

pone.0138932.g006: Measure of time complexity.
Mentions: To explore the influence of time complexity on BNEPD technique, simulations are performed by applying 350 different sensors with a network size of 1000 * 1000 m in a transmission range of 100 ms depicted in Fig 6. The BNEPD technique shows competitive results compared to the state-of-the-art methods, namely DRINA [1] and CBPS [2]. The Fig also shows that the time complexity drastically reduces and reaches its zenith compared to two other methods because of the application of Bayes principle where sensor nodes efficiently detects target objects of similar events by sending it back to the sink nodes. In addition, efficient data aggregation at the sink nodes using polynomial regression function further improves the data aggregation efficiency with the help of polynomial coefficient using Poly Distribution algorithm. The application of Poly Distribution Algorithm efficiently helps in minimizing the time complexity by 4–9% when compared to DRINA [1] and 8–17% when compared to CBPS [2] respectively.

Bottom Line: To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network.Finally, the Poly Distribute algorithm effectively distributes the sensor nodes.Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Nandha Engineering College,Erode, Tamilnadu.

ABSTRACT
Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

No MeSH data available.


Related in: MedlinePlus